Analysis of Factors Affecting Fiscal Revenue in Guangxi Zhuang Autonomous Region
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v5i5.2876
Abstract
Based on the fiscal revenue data and related economic indicators of Guangxi Zhuang Autonomous Region from 1994 to 2022, this paper explores the main influencing factors of fiscal revenue in Guangxi Zhuang Autonomous Region. The first step is to test the correlation and multicollinearity between the variables. According to the test results, there is a strong multicollinearity among the independent variables. Therefore, the variables need to be screened. Ridge regression, lasso regression and adaptive lasso regression are used for variable selection in this paper. The three models are then evaluated and it is concluded that the lasso regression model provides the best fit. According to the lasso model, the factors that have a more pronounced impact on fiscal revenue are: tax revenue, total retail sales of consumer goods, education expenditure and the number of college graduates. Finally, relevant suggestions are made for the selected key factors to increase Guangxi's fiscal revenue.
Keywords
ridge regression; lasso regression; adaptive lasso regression; fiscal revenue
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[3] He Xueping, Li Xingxu. Analysis of factors affecting fiscal revenue in Yunnan Province [J]. China Market, 2017, 19:47-51.
[4] Dong Xiaogang, Diao Yajing, Li Huiling, et al. Analysis of fiscal revenue factors under Ling regression, LASSO regression and Adaptive-LASSO regression [J]. Journal of Jilin Normal University, 2018, 39 (2): 45-53.
[5] Wu Xizhi. Statistical methods of complex data [M]. Beijing: Renmin University of China Press, 2012.
[6] Feng Haiqi, Zhao Yumei, Wang Linlin. Analysis of influencing factors of retail sales of social consumer goods in Shandong Province-based on Lasso regression model [J]. Journal of Ludong University (Natural Science Edition), 2021, 37 (4): 310-314.
[7] He Xiaoqun, Liu Wenqing. Applied Regression Analysis [M]. 4th edition, Beijing: Renmin University of China Press, 2015.
[8] Hu Yuwen. Analysis of influencing factors of R&D investment intensity in universities in Jiangxi Province based on LASSO regression [J]. Science and Technology and Industry, 2020, 20 (5): 84-88.
[9] Zhu Hailong, Li Pingping. Analysis of influencing factors of fiscal revenue in Anhui Province based on Ridge regression and LASSO regression [J]. Journal of Jiangxi University of Science and Technology, 2022, 43 (1): 59-65.
[10] Ji Chao. Evaluation of influencing factors of my country's fiscal revenue and its forecasting methods [J]. Local Finance Research, 2016 (2): 41-46.
[11] Wang Qi, Guo Shuang. Forecast analysis of fiscal revenue in Gansu Province [J]. Chinese Market, 2018 (28): 39-40.
[12] Zhao Xufang, Lu Wei. Empirical study on taxation influencing factors based on stepwise regression method [J]. China Township Enterprise Accounting, 2020 (08): 25-27.
[13] Yu Li. Statistical analysis of factors affecting China's fiscal revenue [J]. Journal of Qinghai University (Natural Science Edition), 2015, 33 (03): 90-93+100.
[14] Shuanghua. Fiscal revenue forecast of Hebei Province based on grey GM (1, N) model [J]. Journal of Shijiazhuang University, 2018, 20 (01): 18-23.
[15] Sun Yuan, Lu Ning. Local fiscal general budget revenue forecast model and empirical analysis [J]. Research on Quantitative Economics and Technology Economics, 2007 (01): 38-45.
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